Detection of Covert Timing Channels with Machine Learning Methods Using Different Window Sizes
| Title | Detection of Covert Timing Channels with Machine Learning Methods Using Different Window Sizes |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Karadoğan, İsmail, Karci, Ali |
| Conference Name | 2019 International Artificial Intelligence and Data Processing Symposium (IDAP) |
| Date Published | Sept. 2019 |
| Publisher | IEEE |
| ISBN Number | 978-1-7281-2932-7 |
| Keywords | composability, compositionality, computer network security, covert channels, covert timing channel, data packets, feature extraction, hidden data, Information security, learning (artificial intelligence), Linux, machine learning, machine learning methods, network steganography, Protocols, pubcrawl, resilience, Resiliency, Scalability, TCPIP, telecommunication channels, Timing, Vectors, window sizes |
| Abstract | In this study, delays between data packets were read by using different window sizes to detect data transmitted from covert timing channel in computer networks, and feature vectors were extracted from them and detection of hidden data by some classification algorithms was achieved with high performance rate. |
| URL | https://ieeexplore.ieee.org/document/8875875 |
| DOI | 10.1109/IDAP.2019.8875875 |
| Citation Key | karadogan_detection_2019 |
- machine learning methods
- window sizes
- Vectors
- timing
- telecommunication channels
- TCPIP
- Scalability
- Resiliency
- resilience
- pubcrawl
- Protocols
- network steganography
- composability
- machine learning
- Linux
- learning (artificial intelligence)
- information security
- hidden data
- feature extraction
- data packets
- covert timing channel
- covert channels
- computer network security
- Compositionality